Data models for defining data transmission workflow and facilitating data communication

ABSTRACT

A computing device for collecting and preserving data acquired from various devices in a data model with the respective context of acquired data. The computing device may provide a user interface to receive the context or information model associated with a dataset. By providing data with its context, different software platforms may synthesize or analyze the retrieved data more efficiently. Moreover, the computing device may include transaction conditions to define a workflow for transferring the datasets using data model associated with one or more datasets for transmission of data to a destination. The transaction conditions may detail a custom workflow for data communication through an industrial automation system using the data model.

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims benefit of U.S. Provisional Patent ApplicationNo. 62/937,248, each filed on Nov. 18, 2019, and each hereinincorporated by reference in its entirety.

BACKGROUND

The present disclosure relates generally to systems and methods forcollecting context of data stored on industrial automation components,such as controllers, devices, and the like. In particular, the presentdisclosure is related to systems and methods for employing aninformation gateway component that may move data along with valuesassociated with the data when data is requested from a component.

This section is intended to introduce the reader to various aspects ofart that may be related to various aspects of the present techniques,which are described and/or claimed below. This discussion is believed tobe helpful in providing the reader with background information tofacilitate a better understanding of the various aspects of the presentdisclosure. Accordingly, it should be understood that these statementsare to be read in this light, and not as admissions of prior art.

An industrial automation system may include an industrial automationlayer including a number of industrial automation components. Theindustrial automation components may include a wide range of components,such as valves, electric motors, a wide range of sensors, other suitablemonitoring devices, or the like. The industrial automation componentsmay provide data indicative of information or status therefrom.Moreover, the industrial automation components may include programmingterminals, automation controllers, input/output (I/O) modules,communication networks, human-machine interface (HMI) terminals, and thelike, to receive statuses and/or information in the form of data. Theindustrial automation system may provide the received statuses and/orinformation in various informative formats to an operator, such asalerts to change or adjust operation of one or more components of theindustrial automation system or adjusting operation of one or moreactuators, to manage the industrial automation system, or the like.

Generally, the networked components described above may be associatedwith information, such as different statuses, sensing data, or the like.The information may relate to an operation of the industrial automationsystem and may be monitored by one or more automation control andmonitoring systems. Certain communication systems are used to transmitthe information to an automation control and monitoring system of theindustrial automation system. For example, each networked device maycommunicate with one or more automation control and monitoring systemsvia wired or wireless communication networks. With this in mind, it maybe useful to improve methods for communication between automationcontrol and monitoring systems and networked devices within industrialautomation systems.

BRIEF DESCRIPTION

A summary of certain embodiments disclosed herein is set forth below. Itshould be understood that these aspects are presented merely to providethe reader with a brief summary of these certain embodiments and thatthese aspects are not intended to limit the scope of this disclosure.Indeed, this disclosure may encompass a variety of aspects that may notbe set forth below.

In one embodiment, an industrial automation system is described. Theindustrial automation system may include multiple devices for performingmultiple operations. Moreover, one or multiple processors may performoperations. The operations include accessing a first device thatcomprises a plurality of datasets, determining whether a first datasetof the plurality of datasets is associated with an information model,receiving one or more inputs indicative of a first information modelassociated with the first dataset in response to the first dataset notbeing associated with the information model, and transferring the firstdataset and the first information model to another device of theplurality of devices.

In another embodiment, a method of operating an industrial automationsystem is described. The method may include using a computing device toperform operations that includes detecting one or more control systemsconnected to the computing device, generating a first visualizationrepresentative of the one or more control systems, receiving a firstinput selecting a first control system of the one or more controlsystems using the first visualization, and generating a secondvisualization representative of a list of data models based on the firstcontrol system. The method may further include receiving a second inputselecting one data model from the list of data models, storing the onedata model in a storage, and generating a third visualizationrepresentative of one or more data destination components. Furthermore,the method may include receiving a third input selecting one datadestination component of the one or more data destination components,and sending, by the computing device, one or more datasets associatedwith the first control system and the one data model to the one datadestination component.

In yet another embodiment, A tangible, non-transitory, machine-readablemedium, comprising machine-readable instructions that, when executed bya processor, cause the processor of an industrial automation system toperform actions. The actions may include detecting one or more controlsystems connected to a computing device, generating a firstvisualization representative of the one or more control systems,receiving a first input selecting a control system of the one or morecontrol systems via the first visualization, and generating a secondvisualization representative of a list of data models based on the onecontrol system. The actions may further include receiving a second inputselecting a data model from the list of data models, storing theselected data model in a storage, generating a third visualizationrepresentative of one or more data destination components, receiving athird input selecting one data destination component of the one or moredata destination components; and sending one or more datasets associatedwith the one control system and the selected data model to the one datadestination component.

DRAWINGS

These and other features, aspects, and advantages of the embodimentsdescribed in the present disclosure will become better understood whenthe following detailed description is read with reference to theaccompanying drawings in which like characters represent like partsthroughout the drawings, wherein:

FIG. 1 illustrates a block diagram representing example hierarchicallevels of an industrial automation system, in accordance with anembodiment presented herein;

FIG. 2 illustrates a block diagram of components within a computingdevice of the industrial automation system of FIG. 1, in accordance withan embodiment presented herein;

FIG. 3 illustrates an example packaging factory employing the industrialautomation system of FIG. 1, in accordance with an embodiment presentedherein;

FIG. 4 illustrates a block diagram of relationships between a computingdevice and control systems that may be employed within the industrialautomation system of FIG. 1, in accordance with an embodiment presentedherein;

FIG. 5 illustrates unstructured raw data that may be transmitted bycontrol systems of FIG. 4, in accordance with an embodiment presentedherein;

FIG. 6 illustrates a hierarchically structured data organized accordingto a data model by the computing device of FIG. 1, in accordance with anembodiment presented herein;

FIG. 7 illustrates a flowchart of a method for defining data structureby the computing device of FIG. 1, in accordance with an embodimentpresented herein;

FIG. 8 depicts an example visualization that presents the connectedcontrol systems to a user, in accordance with an embodiment presentedherein and block 144 in the flowchart of FIG. 7;

FIG. 9 depicts an example visualization that presents a list of datamodels to the user, in accordance with an embodiment presented hereinand block 148 in the flowchart in FIG. 7;

FIG. 10 depicts an example visualization that presents a hierarchicalrepresentation of components of the data model, in accordance with anembodiment presented herein and block 150 in the flowchart in FIG. 7;

FIG. 11 depicts an example visualization that presents available datasources for selection by the user, in accordance with an embodimentpresented herein and block 156 in the flowchart in FIG. 7;

FIG. 12 depicts an example visualization that presents an applicationtab including multiple data destination components, in accordance withan embodiment presented herein and block 160 in the flowchart in FIG. 7;

FIG. 13 illustrates a flowchart of a method for using the computingdevice of FIG. 1 to transmit data organized according to a data model,in accordance with an embodiment presented herein.

DETAILED DESCRIPTION

One or more specific embodiments of the present disclosure will bedescribed below. In an effort to provide a concise description of theseembodiments, all features of an actual implementation may not bedescribed in the specification. It should be appreciated that in thedevelopment of any such actual implementation, as in any engineering ordesign project, numerous implementation-specific decisions must be madeto achieve the developers' specific goals, such as compliance withsystem-related and business-related constraints, which may vary from oneimplementation to another. Moreover, it should be appreciated that sucha development effort might be complex and time consuming, but wouldnevertheless be a routine undertaking of design, fabrication, andmanufacture for those of ordinary skill having the benefit of thisdisclosure. When introducing elements of various embodiments of thepresent disclosure, the articles “a,” “an,” “the,” and “said” areintended to mean that there are one or more of the elements. The terms“comprising,” “including,” and “having” are intended to be inclusive andmean that there may be additional elements other than the listedelements.

The present disclosure relates generally to systems and methods forcollecting data and context of data stored on industrial automationcomponents, such as controllers, devices, and the like. Data models maybe used to detail a relationship between certain, constraints, rules,data, data values, operations, or other types of information. The datamodels may specify relationships between kinds or types of data withrespect to other types of data. As such, the data models may providecontext with regard to how certain datasets are related to otherdatasets. As a result, a stable and organized structure of informationmay be provided to different software platforms, devices, and the like.By way of example, in an industrial automation system that employsoperational technology (OT) systems and information technology (IT)systems, data communicated between the OT systems and the IT systems maynot include the context (e.g., properties) of the data when the data istransmitted. Instead, raw values of the data may be transmitted withoutproviding the appropriate context regarding the data.

With this mind, the embodiments described herein may include acomponent, such as a computing device, that may collect and preserve thecontext of the data acquired from various devices, such that thecomputing device may transmit the acquired data along with the contextof the data. For example, if a data model defines a dataset A asincluding datasets B and C, the computing device may acquire dataset Balong with dataset C when facilitating a request for dataset A. Incertain embodiments, the data model may provide a context with regard torelated datasets. The data model may be defined with respect to thedatasets as SmartTags (e.g., metadata) or another suitable datastructure capable of detailing the relationships between datasets in thedata model. By providing the data model with retrieved datasets, thecomputing device may provide contextual information regardingrelationships between various devices and components in the industrialautomation system and enable a coherent data transfer between devices.

In addition to retrieving datasets with specific data structures relatedto the respective data model, the computing device may provide a userinterface that enables a user to provide the context or informationmodel associated with a particular dataset. In this way, the user mayadd a data model or context to datasets, such that the retrieved datamay continue to be transmitted to other devices with the appropriatecontext.

By providing data with its context, different software platforms maysynthesize or analyze the retrieved data more efficiently. For instance,unstructured component data provided without context may bepre-processed to group relevant datasets together prior to the datasetsbeing analyzed. Moreover, by retrieving the datasets with theappropriate context, the computing device may acquire datasets anddisplay how the datasets are related via a particular context.

In addition to retrieving datasets with SmartTags and/or other datastructures related to the respective data model, the computing devicemay provide a user interface for a user to input transition conditionsor transaction conditions to define a workflow for transferring thedatasets using the context and/or data model associated with one or moredatasets. For instance, the user may describe a workflow using theSmartTags and the transaction conditions to control the transition ofdata between a data generating component of the industrial automationsystem and a data destination component. For example, the user maydescribe a transaction condition by defining a triggering event (e.g.,when data value exceeds 300) for data retrieved from a first data source(e.g., a temperature sensor) to initiate capturing data from a seconddata source (e.g., pressure sensor). In addition, the transactionconditions may define how data will be collected from a data source.That is, the transaction conditions may detail that data is accessedfrom a data source using a particular driver and collection path. Inthis way, the present embodiments described below better enable the userto describe different datasets, associate a dataset to one or more otherdatasets by defining a relationship between the respective datasets,define transaction conditions to detail a custom workflow for datacommunication through an industrial automation system using the datamodel described herein. Additional details with regard to providingcontext with datasets and defining the manner in which the datasets areretrieved from a source and sent to a destination will be describedbelow with reference to FIGS. 1-13.

By way of introduction, FIG. 1 depicts a block diagram embodiment of anexample industrial automation system 10 in which the present embodimentsmay be implemented. The industrial automation system 10 may be anysystem in the material handling, packaging industries, manufacturing,processing, batch processing, or any technical field that employs theuse of one or more industrial automation components. In one embodiment,the industrial automation system 10 may include a factory 12 that mayencompass part of the entire industrial automation system 10. As such,the industrial automation system 10 may include other factories 14 thatmay be employed with the factory 12 to perform an industrial automationprocess or the like.

Each factory 12 (or factory 14) may be divided into a number of areas16, which may include different production processes that use differenttypes of industrial automation components. In one example, one area 16may include a sub-assembly production process and another area 16 mayinclude a core production process. In another example, each area 16 maybe related to a different operation being performed in the manufacturingprocess. For instance, in a jellybean manufacturing system, the areas 16may include a jelly bean making area, a packaging area, a waterfiltration area, and the like. In yet another example, the area 16 mayinclude a production line in which a particular industrial process maybe performed. Referring back to the jellybean manufacturing systemexample, the production line may include a cooking line in which thejelly beans may be created, a sorting line where the jelly beans may besorted according to a respective flavor, and a packaging line where thesorted jelly beans may be packaged into boxes or the like.

The area 16 may also be associated with physical locations of a numberof industrial automation components 20, referred hereinafter ascomponents 20. The components 20 may include a wide range of valves,electric motors, a wide range of sensors, other suitable monitoringdevices, or the like. The areas 16 may also be related to differentdiscipline areas of the industrial automation system 10, such as batchoperation areas, continuous operation areas, discrete operation areas,inventory operation areas, and the like.

The areas 16 may be subdivided into smaller units, or cells 18, whichmay be further subdivided into components 20. Using the exampledescribed above, the sub-assembly production process area 16 may besubdivided into cells 18 that may denote a particular group ofcomponents 20 that may be used to perform one aspect of the sub-assemblyproduction process. As such, the cell 18 may include a portion of thearea 16 such as first part of a production line. The cell 18 may alsoinclude different parts of a particular procedure.

These cells 18 may then be further subdivided into components 20, whichmay correspond to individual industrial automation components, such ascontrollers, input/output (I/O) modules, motor control centers, motors,human machine interfaces (HMIs), operator interfaces, contactors,starters, sensors, drives, relays, protection devices, switchgear,compressors, network switches (e.g., Ethernet switches, modular-managed,fixed-managed, service-router, industrial, unmanaged, etc.) and thelike. Although the factory 12, the factory 14, the areas 16, and thecells 18 are termed as factories, areas, and cells, it should be notedthat in various industries these groupings may be termed differently.

The components 20 may also be related to various industrial equipmentsuch as mixers, machine conveyors, tanks, skids, specialized originalequipment manufacturer machines, and the like. The components 20 mayalso be associated with devices used by the equipment such as scanners,gauges, valves, flow meters, and the like. In one embodiment, everyaspect of the component 20 may be controlled or operated by a singlecontroller (e.g., control system). In another embodiment, the controland operation of each aspect of the component 20 may be distributed viamultiple controllers (e.g., control sy stem).

The components 20 may be used within the corresponding cell 18, area 16,and/or factory 12 to perform various operations for the respective cell18, area 16, and/or factory 12. In certain embodiments, the components20 may be communicatively coupled to each other, to an industrialcontrol system 22, or the like. In some embodiments, components 20 mayinclude routers, switching gateways, and other common devices that mayfacilitate the communicatively coupling of the components 20.Additionally, the industrial control system 22, referred hereinafter asthe control system 22, may also be communicatively coupled to one ormore sub-systems that may monitor and/or control the operations of eachrespective cell 18, area 16, or factory 12.

In one embodiment, the control system 22 may include a computationdevice that may include communication abilities, processing abilities,and the like. For example, the control system 22 may be a controller,such as a programmable logic controller (PLC), a programmable automationcontroller (PAC), or any other controller that may monitor, control, andoperate an industrial automation component 20. In other embodiments, thecontrol system 22 may be incorporated into one or more components 20(e.g., edge computation devices) or may be implemented as a stand-alonecomputation device (e.g., general purpose computer), such as a desktopcomputer, a laptop computer, a tablet computer, a mobile devicecomputing device, or the like.

In certain embodiments, the control system 22 may be implemented withindevices and enable components 20 to connect and communicate with eachother. For instance, the control system 22 may be implemented withinnetwork routers and/or switches. In this manner, the network routersand/or switches may host the control system 22 to control and operatethe components 20 and may be communicatively coupled to a respectivenetwork router and/or switch. Since network routers and/or switches mayserve as a hub for data transfers between the components 20, the controlsystem 22 embedded within the routers and/or switches may bestrategically positioned within a data network to have access or receivedata associated with various components 20. As such, the control system22 may perform various types of analyses on the received data and maythen control and operate the respective components 20 more efficientlyor effectively based on the results of the analysis.

In addition to the physical devices mentioned above, the control system22 may include a software-based emulation of any of the aforementionedphysical devices. For example, the control system 22 may be implementedas software modules that may perform similar operations as certainhardware controllers, devices, and the like. As such, the control system22 may create virtual instances of the hardware components (e.g.,controllers, I/O modules). These virtual instances may provide moreflexible ways in which the control system 22 may be implemented tomonitor and control the components 20.

In one embodiment, the control system 22 may be implemented virtually ina cloud-accessible platform (i.e., cloud-computing system), one or moreservers, in various computing devices (e.g., general purpose computers),and the like. As such, the control system 22 may operate as a softcontroller or as a control engine running in the cloud-computing system.By virtually implementing the control system 22 in a cloud-computingsystem, the control system 22 may use a distributed computingarchitecture to perform various analyses and control operations. As moredata associated with the components 20, the cells 18, the areas 16, andthe factories 14 become available, the distributed computingarchitecture in the cloud-computing system may enable the control system22 to provide data analysis more efficiently. That is, since thecloud-computing system may incorporate numerous computing systems andprocessors to perform the data analysis, the results of the analysis maybe available more quickly. In this way, the respective operations of thecomponents 20, the cells 18, the areas 16, and the factories 14 may becontrolled in real-time or near real-time.

Keeping the foregoing in mind, it should be understood that the controlsystem 22, as mentioned throughout this disclosure, may be implementedas physical components (e.g., hardware-based) and/or virtual components(e.g., software-based) used to monitor and/or operate the components 20,the cells 18, the areas 16, and the factories 14. Moreover, by providingthe ability to incorporate the control system 22 into various types ofenvironments, the industrial automation system 10 may be well suited toexpand and grow with the addition of new components 20.

In certain embodiments, a computing device 24 may be connected to one ormultiple control systems, such as the control system 22. The computingdevice 24 may receive data from the one or multiple control systemsassociated with the respective components 20. The computing device 24may provide structure to the received data, for example by allocatingthe received data to datasets according to a data model. The computingdevice 24 may use data models to provide context to the received datafrom the control system 22. In some embodiments, the computing device 24may receive data from components 20 between multiple cells 18, multipleareas 16, and/or different factories 12 and/or 14. The computing device24 described herein may be referred to as the information gateway,gateway, edge computing device, or by other names in differentembodiments.

In some embodiments, the computing device 24 may be implemented intodifferent physical devices, such as control system 22 and/or component20, network routers and/or switches, or a stand-alone computing device(e.g., general purpose computer), such as a desktop computer, a laptopcomputer, a tablet computer, a mobile device computing device, or thelike. In other embodiments, the computing device 24 may be implementedas a controller, such as a programmable logic controller (PLC), aprogrammable automation controller (PAC), or any other controller thatmay monitor, control, and operate an industrial automation device orcomponent. Additionally, the computing device 24 may include asoftware-based emulation of any of the aforementioned physical devices.

As mentioned above, the computing device 24 may be a controller or anycomputing device that may include communication abilities, processingabilities, and the like. FIG. 2 illustrates a detailed block diagram 30of components in the computing device 24 that may be used to perform thetechniques described herein.

Referring now to FIG. 2, the computing device 24 may include acommunication component 32, a processor 34, a memory 36, a storage 38,input/output (I/O) module 40 including I/O ports, a display 42, and thelike. The communication component 32 may be a wireless or wiredcomponent that may facilitate communication between the components 20,the control system 22 of the cell 18, the area 16, the factory 12 orfactory 14, and the like.

The communication component 32 may be a wireless or wired communicationcomponent that facilitates communication between the computing device 24and other suitable electronic devices. The processor 34 may be any typeof computer processor or microprocessor capable of executingcomputer-executable code. The processor 34 may also include multipleprocessors that may perform the operations described below.

The memory 36 and the storage 38 may be any suitable articles ofmanufacture that can serve as media to store processor-executable code,data, or the like. These articles of manufacture may representcomputer-readable media (i.e., any suitable form of memory or storage)that may store the processor-executable code used by the processor 34 toperform the presently disclosed techniques. In some embodiments, thememory 36 may include a volatile data storage unit, such as arandom-access memory (RAM) and the storage 38 may include a non-volatiledata storage unit, such as a hard disk. The memory 36 and the storage 38may also be used to store the data, data model, and the like. The memory36 and the storage 38 may represent non-transitory computer-readablemedia (i.e., any suitable form of memory or storage) that may store theprocessor-executable code used by the processor 34 to perform varioustechniques described herein. It should be noted that non-transitorymerely indicates that the media is tangible and not a signal.

The computing device 24 may also include an input/output (I/O) module40. The I/O module 40 may enable the computing device 24 to communicatewith various devices in the industrial automation system. Moreover, theI/O module 40 may enable the computing device 24 to receive data fromthe control system 22 and/or other control systems. The I/O module 40may be interfaces that may couple to other peripheral components such asinput devices (e.g., keyboard, mouse), sensors, input/output (I/O)modules, and the like.

The display 42 may operate to depict visualizations associated withsoftware or executable code being processed by the processor. In oneembodiment, the display may be a touch display capable of receivinginputs from a user. For example, the display 42 may be any suitable typeof display, such as a liquid crystal display (LCD), plasma display, oran organic light emitting diode (OLED) display. Additionally, in oneembodiment, the display 42 may be provided in conjunction with atouch-sensitive mechanism (e.g., a touch screen) that may function aspart of a control interface. The display 42 may provide a user withinformation about the data received via the communication component 32.The information may include data received from control system 22 orother control systems and may be associated with various components. Thedisplay 42 may also be used by a user to provide input to the computingdevice 24, such as defining data models with the respective datastructures querying for certain data to be collected from variouscomponents of the factory 12 among other things.

It should be noted that the components described above with regard tothe computing device 24 are by way of example and the computing device24 may include additional or fewer components as shown. Although theblock diagram 30 is depicted with respect to the computing device 24, itshould be noted that the computing device 24 may be associated with anysuitable computing system described herein. It also should be notedthat, the computing device 24 or other suitable components may includeall or some of the described components to perform the varioustechniques described herein.

An example industrial automation system 10 of a packaging factory 50 andhow the packaging factory 50 may be divided and sub-divided into areas16 and cells 18 are depicted in FIG. 3. As illustrated in FIG. 3, thepackaging factory 50 may represent an exemplary high-speed packagingline that may be employed in the food and beverage industry that mayprocess beverage containers (i.e., a beverage line). As such, thepackaging factory 50 may include industrial automation components that,for example, may enable machine components to fill, label, package, orpalletize containers. The packaging factory 50 may also include one ormore conveyor sections that may transport, align, or buffer containersbetween the machine components. Although FIG. 3 illustrates a packagingfactory, it should be noted that the embodiments described herein arenot limited for use with a packaging factory. Instead, it should beunderstood that the embodiments described herein may be employed in anyindustrial automation environment.

As illustrated in FIG. 3, the packaging factory 50 may include machinecomponents configured to conduct a particular function with respect tothe beverage packaging process. For example, the beverage packagingprocess begins at a loading station 52, where pallets of empty cans orbottles to be filled are fed into packaging factory 50 via a conveyorsection 54. The conveyor section 54 transports the empty cans from theloading station 52 to a washing station 56, where the empty cans andbottles are washed and prepared for filling. As the washed cans andbottles exit the washing station 56, the conveyor section 54 maygradually transition into an aligning conveyor section 58, such that thewashed cans and bottles enter a filling and sealing station 60 in asingle-file line.

The filling and sealing station 60 may function at an optimal rate whenthe washed cans and bottles enter the filling and sealing station 60 ina steady, uniform stream. However, if the transition between theconveyor section 54 and the aligning conveyor section 56 is erratic orfaster than desired, the filling and sealing station 60 may not functionat an optimal rate. As such, optimizing performance parameters (e.g.,speed, size, function, position/arrangement or quantity) of the conveyorsections (i.e., conveyor section 54 or aligning conveyor section 58) maybe beneficial to the efficiency of the packaging factory 50.

As the sealed cans exit the filling and sealing station 60, a bufferingconveyor section 62 may hold the sealed cans to delay their entry intothe next station. In addition, the buffering conveyor section 62 maytransport the sealed cans in a single-file line so that the sealed cansarrive at a sterilization station 64 or a labeling station 66 at adesired time with the desired quantity of cans. Similar to the fillingand sealing station 60, the packaging station 64 or the labeling station66 functions efficiently when the buffering conveyor section 62 operatesat optimal performance parameters (e.g., optimal speed, size, function,position/arrangement or quantity). After the cans and bottles have beensterilized and/or labeled, they are packaged into cases (e.g., 6-pack,24-pack, etc.) at a packaging station 68, before they are palletized fortransport at station 70 or stored in a warehouse 72. Clearly, for otherapplications, the particular system components, the conveyors and theirfunction will be different and specially adapted to the application.

The packaging factory 50 may also include the computing device 24 andthe control system 22, which may be located in a control room 74,distributed onto one or more sensors 76, and/or the like. The controlsystem 22 may be coupled to the one or more sensors 76, which maymonitor various aspects of the machine components or conveyor sectionsof the packaging factory 50. The sensors 76 may include any type ofsensor, such as a pressure sensor, an accelerometer, a heat sensor, amotion sensor, a voltage sensor, and the like. The sensors 76 may belocated in various positions within the packaging factory 50 and maymeasure a parameter value of interest relating to the beverage packagingprocess during the operation of the packaging factory 50. For example,in certain embodiments, the sensors 76 may include sensors configured tomeasure the rate of bottles or containers per minute (BPM) entering orleaving a machine component (i.e., stations 54, 56, 58, 64, 66, 68 or70), or the rate of accumulation of bottles on a portion of a conveyorsection (e.g., conveyor section 54 or 62). In general, any sensors 76capable of measuring a parameter value of interest relating to thebeverage packaging process of the packaging factory 50 (e.g., rate,pressure, speed, accumulation, density, distance, position/arrangement,quantity, size, and so forth) may be used.

In some embodiments, the packaging factory 50 may include a number ofindustrial automation power components 78 that may be used to controlpower used by various machine components in the packaging factory 50.The power components 78 may include devices, such as drives, motors,inverters, switch gear, and the like, which may be used to operate acorresponding machine component. For example, the conveyor section 54may rotate using a motor, which may be controlled via a power component78, such as a variable frequency drive.

The power component 78 may include a control system 22 that may monitorand control the operations of the respective power component 78. Assuch, the power component 78 may correspond to the component 20described above with respect to FIG. 1. Referring back to the exampleabove, the control system 22 of the power component 78, such as thedrive used to control the motor rotating the conveyor section 54, maymonitor a voltage provided to the motor and may determine the speed atwhich the conveyor section 54 may be moving. In one embodiment, thecontrol system 22 of the power component 78 may send the data related tothe speed of conveyor section 54 to the control system 22, or to othercontrol systems that may control other components 20. In this manner,the control system 22 or to other control systems may be aware of theoperations of the power component 78 and may account for theseoperations when determining how its respective component should operate.

Keeping the packaging factory 50 of FIG. 3 in mind, the control system22 may receive data from multiple power components 78 dispersedthroughout the packaging factory 50. In some embodiments, the controlsystem 22 may contextualize the received data with respect topre-defined scopes or hierarchical levels. In other embodiments, thecomputing device 24 may query for data from the control system 22 andmay contextualize the data according to different data models asdescribed above. For example, FIG. 4 illustrates a communication network100 in which the computing device 24 of the packaging factory 50 may becommunicatively coupled to multiple components 20 and/or theirrespective control systems 22.

In one embodiment, the scopes of the packaging factory 50 may becategorized based on functions of the components 20 and/or the cells 18of the packaging factory 50. For instance, referring to FIG. 3, theloading station 52 may be categorized as cell 1, the washing station 56may be categorized as cell 2, the sealing station 60 may be categorizedas cell 3, the sterilization station 64 may be categorized as cell 4,the labeling station may be categorized as cell 5, and the packagingstation 68 may be categorized as cell 6.

In some embodiments, a user may define, access, and/or modify a datamodel 108 via the computing device 24. The user may include a factoryoperator personnel and may use a data destination component 118. Thedata destination component 118 may include a user interface and a datacenter, such as a local data center 110 or a cloud-based data center112.

Keeping the foregoing in mind, the computing device 24 may use thecommunication component 32 to facilitate operations of the communicationnetwork 100. For example, the computing device 24 may use thecommunication component 32 to communicate with one or more controlsystems 22, such as a control system 102, a control system 104, and/or acontrol system 106. The control system 22 may monitor and/or control theoperations of a component 20 or a collection of components 20 in a cell18, an area 16, or a factory 12. For example, the control system 102,104, and/or 106 may receive data or information from assets,controllers, and the like (e.g., the components 20) that may be locatedin the cells 18, the areas 16, or the factory 12. The computing device24 may then receive the data collected from the control systems 102,104, and 106 by using the communication component 32.

In one embodiment, the computing device 24 may receive data related tohow the industrial automation system 10 may be subdivided, how each area16, cell 18, and the various components 20 may interact with each other,which components 20 are part of each factory 12, area 16, or cell 18, orthe like. For example, each area 16 may be related to a particularmanufacturing process. As such, the data received by the computingdevice 24 may be processed or contextualized according to the data model108. For example, the data model 108 may represent the received data aspart of other datasets, under different labels, and/or in differenthierarchy levels of a data structure hierarchy.

In certain embodiments, the computing device 24 may present the receiveddata with context and in the form of the data model 108. The controlsystems 102, 104, and/or 106 may each identify a relationship of the oneor more components 20 to a respective cell 18 or area 16 based on thedata model 108. Subsequently, the control systems 102, 104, and/or 106may provide the identified relationships to the computing device 24.

For instance, the computing device 24 may receive data from controlsystems 102, 104, and 106, each associated with different components 20.Upon receiving the data associated with the components 20, the computingdevice 24 may identify a data model, such as the data model 108,associated with the received data. The computing device 24 may thenprovide a representation of the received data according to the datamodel 108, thereby providing a user with context regarding the receiveddata. For example, the data model 108 may indicate that the receiveddata is associated with the factory 12, the area 16, the cell 18, and/orthe component 20.

The data model 108 may be defined to process the received dataassociated with specific components 20. Moreover, the computing device24 may use the data model 108 to extract specific details of eachcomponent 20. That is, the computing device 24 may process the receiveddata to provide context to datasets received from each industrialcomponent, such as speed, flow, temperature, and acceleration, amongother variables. In addition, the data model 108 may providecontextualized data including associations or relationships with otherdevices, systems, plants, servers, types of devices, or other categoriesto classify the received data.

In some embodiments, the data model 108 may be pre-defined in thestorage 38 of the computing device 24. The data model 108, a portion ofthe data model 108, or a component associated with the model 108 may betransmitted from the control systems 102, 104, and/or 106 to thecomputing system 24. In certain embodiments, a user may define the datamodel 108 for received data via a user interface of computing system 24,for example by using the display 42. The computing device 24 may receiveinstructions definitive of a data model 108, the computing device 24 maystore the received data model 108 on the storage 38, and may use theuser-defined data model 108 to organize the received raw data 114.Subsequently, the computing device 24 may provide the structured data116 to the destination component 118 and/or the user in response toreceiving the request for information (e.g., speed data, flow data, andtemperature data).

The data model 108 may provide structure to the received raw data 114,such that the received raw data 114 may be provided to the user in theform of structured data 116. The structured data 116 may includedatasets and/or one or more hierarchal representations of the datasets.The data model 108 may also be incorporated into a workflow that mayinclude transaction conditions and conditional transactions betweencomponents of the data model 108 while providing the structured data 116with the transferred datasets. In some embodiments, the user may definesuch transactions by determining one or more aspects of the datasetsbased on the data model 108 via the computing device 24. In differentembodiments, the user may define the transactions by specifying how thedatasets are to be retrieved and transferred based on one or morerelationships between the datasets of the data model 108. For example,the user may define a transaction to retrieve datasets from datacomponents of a data model associated with a data source, andtransferring the retrieved datasets to data components of a differentdata model that may be part of the data destination component. Thedifferent data model may be data model provided by a third partyprovider in the local data center 110 or the cloud-based data center 112to facilitate the transfer.

The datasets may correspond to different factories, areas, cells,components, and/or properties of components, among other things, asshown in more detail in FIG. 6. The relationships of the datasets maycorrespond to how different factories, areas, cells, and/or componentsare related to each other. For example, in a hierarchical representationof the datasets, a factory dataset may include one or more areadatasets.

The computing device 24 may then provide structured data 116 to thelocal data center 110 or the cloud-based data center 112. For example,the computing device 24 may receive a request for information andprovide contextualized data in response to receiving the request usingthe data model 108. The computing device 24 may provide thecontextualized data to a data center or the user. That is, the computingdevice 24 may provide a portion of the structured data 116 to the datacenter or the user in response to receiving the request for information(e.g., speed data, flow data, and temperature data).

By the way of example, FIG. 5 illustrates raw data 114 that may betransmitted from the control systems 102, 104, and/or 106 to thecomputing system 24. The raw data 114 may be unstructured and mayinclude all the data provided by the control systems 102, 104, and 106.Since the raw data 114 is unstructured, processing the raw data 114 mayprove to be comprehensive and computationally expensive due to the lackof structure or organization.

On the other hand, FIG. 6 depicts an example of structured data 116organized according to the data model 108. The data structure 116 may beassociated with the hierarchy levels of the data model 108 and therespective data sources, such as control systems 102, 104, and/or 106.As such, hierarchical representation of the data structure 116 mayinclude different datasets 120 in hierarchical levels corresponding todifferent factories 12 or 14, areas 16, cells 18, components 20,properties of individual components 20, and other properties of one ormore datasets to name a few examples. Indeed, the data structure 116 maydetail a relationship between datasets 120 with respect to hierarchy,dependencies between datasets 120, and the like.

In some embodiments, the computing device 24 may also receivetransaction data 122 related the structured data 116. The transactiondata 122 may include event driven conditions that specify one or moreconditions in which data is to be transmitted to other components.Moreover, the transaction data 122 may specify details that helpfacilitate a dataset transaction between a data source and a datadestination. The transaction data 122 may be received based on aselection of a driver or a data collection scheme/format to retrievedata from a data source received by a user input. In this way, thedriver may detail how transactions between different components are tobe facilitated. In one embodiment, a user may select a driver thatrepresents the manner (e.g., format) in which the requested datasets areto be retrieved from a data source. By way of example, the driver may bedefined as FactoryTalk Live Data, EtherNet/IP (Common IndustrialProtocol (CIP)), OPC Direct Access (e.g., machine to machinecommunication protocol for industrial automation developed by the OPCFoundation), or any suitable communication protocol. In someembodiments, the transaction data 122 may be defined for each componentor each type of component that may be associated with the factories,areas, cells, and the like. In addition to the communication protocol,the transaction data 122 may include one or more defined rules,relationships, and/or triggering events that characterize how datasetsare stored the data model 108.

The hierarchy representation of the structured data 116 may bepre-defined, user-defined, or modifiable by a user by the way of agraphical user interface (GUI) visualization as described in more detailbelow. It should be understood that the visualization is describing oneembodiment and the interaction between a user and the computing device24 may be provided by any viable interface.

With the forgoing in mind, FIG. 7 illustrates a procedure 140 forcontextualizing raw data according to a data model, such as the datamodel 108. The procedure 140 may be performed by the computing device 24or any suitable computing device for defining datasets 120 and/or thetransaction data 122. It should be understood that the order of theprocedure 140 is provided by way of example and the procedure 140 may beperformed in any suitable order.

Referring now to FIG. 7, at block 142, the computing device 24 maydetect the one or multiple control systems 22, such as control systems102, 104, and/or 106 of the FIG. 4. Control systems 22 maycommunicatively couple to the computing device 24 using wired connectionor wireless connection. In different embodiments, the computing device24 may detect the control system 22 upon connection, for example by theway of a pre-installed driver on the computing device or a respectivedriver module for the connected control system 22.

At block 144, after detection of the one or multiple connected controlsystems 22, the computing device 24 may present the connected controlsystems 22 via a display. For example, the computing device 24 mayprovide a list of all the detected control systems 22 as illustrated invisualization 170 of FIG. 8. The visualization 170 may include detectedcontrol systems 22 and/or other viable sources of data represented forselection by the user, when a data sources tab 194 is selected. That is,the user may define the data model 108 using the data sources presentedby the visualization 170. In some examples, the sources of data in thevisualization 170 are auto-detected, whereas in other examples, thevisualized sources of data or at least a number of visualized sources ofdata are configured by the user.

Referring to FIG. 8, the visualization 170 may provide the user withadditional functionality. The additional functionality may includeadding new control systems using an input visualization 172, removing adetected control system using an input visualization 174, refreshing thelist of control systems using an input visualization 176, clearing thelist of control systems using an input visualization 178, and/or editingproperties of the detected control system using an input visualization180. Referring back to FIG. 7, at block 146, the computing device 24 mayreceive input indicative of a selection of a detected control system 22as a first source of data. After receiving the selection, the computingdevice 24 may access the selected control system 22 and receive raw data114 associated with the selected control system 22.

At block 148, the computing device 24 may present a list of data models108 that may be used for contextualizing data associated with theselected control system 22 at block 146. FIG. 9 may depict an embodimentof a visualization 190 that provides an example list of data models 108selectable by the user via display 42.

The visualization 190 may include a configuration tab 192 including oneor multiple child tabs. For example, the child tabs may include the datasources tab 194, a models tab 196, and an applications tab 198. The datasources tab 194 may include one or multiple control systems 22selectable by the user to identify sources of data. The models tab 196may include the data models 108 selectable by the user to be used withthe selected sources of data (e.g., one or multiple control systems 22).The applications tab 198 may include the destination components 118where the structured data 116 may be sent. The models tab 196 and theapplications tab 198 are discussed in more details below. It should beappreciated that in different embodiments, a visualization forcontextualizing raw data according to a data model may includeadditional or fewer tabs, may visualize a single tab including differentportions associated with different information such as selectable datasources, selectable data models, and/or selectable data destinationcomponents or applications to be used.

Referring back to FIG. 9, the models tab 196 may include multiple datamodels 206 available for selection by the user. For example, the usermay select the data model 108 to be used with a selected control system22, as depicted in the FIG. 9. Furthermore, a user may create datamodels via add data model feature 200, remove existing data models viadelete data model feature 202 and/or edit the existing data models 108via edit data model feature 204 of the visualization 190. The data model108 may define a hierarchy or relationship between different datasets inthe data model 108

At block 150, the computing device 24 may receive input to create a newdata model for the selected control system. The user may use the adddata model feature 200 of visualization 190 to create the data model108. The add data model feature 200 may prompt the user to providedetails for the new data model 108. For instance, the add data modelfeature 200 may prompt the user to a visualization 210 depicted in FIG.10 and may include an example of tools provided to the user for creatinga hierarchical representation 134 associated with components of the datamodel 108. In some embodiments, one or multiple properties associatedwith the data source, the detected control system, the respectivesensor, and/or the industrial automation component may be configured,re-configured, and/or used as a triggering event by the user via aproperties pane 220 described with respect to FIG. 10.

The visualization 210 may include the sources of data, such as the oneor multiple control systems 22 (e.g., as described with respect tovisualization 170), which may be represented by tags 216 (e.g.,SmartTags). A dataset or a portion of a dataset of the one or multipledatasets 120 may be represented by the tags 216. For example, the usermay use an input visualization 218 to add and/or describe the tags 216to represent a control system 22 or a portion of data sourced from thecontrol system 22. The visualization 210 may also include the data model108, for example selected previously in the visualization 190 by theuser, or defined by the user using the add data model feature 200.Moreover, the visualization 210 may include the properties pane 220including one or multiple properties associated with a selected datasource (e.g., by selecting a data source) or a selected component of thedata model 108 (e.g., node 1 or child 2).

In some embodiments, the user may select a component 222 of the datamodel 108 using the visualization 210 and one or multiple properties 224associated with the selected component 222 may be provided to the uservia the properties pane 220. The selected component 222 may be thedataset 120, and may include the transaction data 122, among othercomponents. The properties 224 may include different values associatedwith the selected component 222, values associated with datasetsassociated with the selected component 222, the transaction conditionsassociated with the selected component 222, or other propertiesassociated with the selected component. For example, the properties 224may include a visualization of values of datasets associated with theselected component 222. Moreover, the properties pane 220 may includeproperties associated with the transaction data 122. That is, theproperties pane 220 may provide a visualization of transaction data 122,including event driven conditions that specify one or more conditions inwhich data associated with selected component 222 may be transmitted toother components, one or more defined rules, relationships, and/ortriggering events that characterize how datasets associated with theselected component 222 are stored the data model 108, and/or otherproperties associated with the selected component 222. The user maydefine and/or modify the transaction data (e.g., transaction data 122)using the properties pane 220.

At block 152, the computing device 24 may receive input to definecomponents of the data model 108. The visualization 210 may include anadd component feature 212 and a remove component feature 214 that mayadd and remove components to the data model 108. By the way of example,the user may use the add component feature 212 to define a parentcomponent “node 1” and a child component “child 2”. For example, theparent component “node 1” may be defined as a parent component thatincludes the child component “child 2” as described below.

At block 154, the user may receive input to define a data structure,such as the hierarchical representation 134, associated with a selectedpart of the data model 108. For example, the user may associate datamodel component “node 1” to the data model component “child 2”, suchthat the data model component “child 2” is represented as being a partof the data model component “node 1”, as depicted in FIG. 10 as part ofthe hierarchical representation 134. In this way, the user is enabled todefine the hierarchical representation 134 of the structured data 116.That is, the user may bind tags to associate the data model componentsby using different features in different embodiments, such as drag anddropping the tags 216 to hierarchical level in the hierarchicalrepresentation 134 to associate datasets to other components. Indifferent embodiments related to the described methods, the user mayassociate different number of data model components to define thehierarchical representation 134. It should be noted that components ofthe data model 108 may include the datasets 120 (e.g., represented bythe tags 216) along with transaction data 122. The user may describe aworkflow that specifies how the datasets 120 and the transaction data122 is used.

In such embodiments, the user may define one or multiple datasets 120and/or the transaction data 122 for each of the hierarchical levels ofthe data model 108, for particular datasets in the data model 108, fordifferent data sources in the industrial automation system 10, and thelike. The transaction data 122 may include triggering events definedwith respect to properties 220 of a selected component of the data model108. The workflow may be defined using transaction data (e.g.,transaction data 122) with transaction conditions that may define arelationship between the components of the data model 108, and/orbetween the components of the data model 108 and other data modelsand/or data destination component 118. The workflow may include one ormultiple triggering events, conditional relationships, or a combinationof both, using the properties 224 of a selected component (e.g., theselected component 222). For example, one or multiple conditions (e.g.,temperature to exceed 200 degrees) may be satisfied with respect toproperties of the retrieved data in order for the computing device 24 toperform certain actions (e.g., data transfer, control equipment) withrespect to the retrieved data or other components in the industrialautomation system 10. The workflow may also automate a process internalto the components of the data model 108 and/or by mapping the componentsof the data model 108 to one or multiple external data models.

Moving on to block 156, the computing device 24 may receive input toassociate the raw data 114 of the selected control system 22 to a partof data model 108 and/or one or more data model components. By the wayof example, a user may select data model component “node 1” and the datasources tab 194 to select one or more data sources (e.g., the selectedcontrol system 22) to be associated with the data model component “node1”. Multiple tags 216 may represent available data sources configured,for example, using the visualization 170 of FIG. 8. That is, the usermay select one or more data sources from an available data sourceswindow, as depicted in visualization 170 of FIG. 8, to be associatedwith the data model component “node 1”. The user may repeat this processfor “child 2” and other components of the data model 108.

At block 158, the computing device 24 may store the defined model(s) inthe storage 38. The data model may be saved on the memory 36 or storage38 of the computing device 24.

At block 160, the computing device 24 may present the available datadestination components 118 in which the data, data model 108, or bothmay be sent, in response to the applications tab 198 is selected. Forexample, FIG. 11 may include a visualization 240 that may depict theapplication tab 198 of the configuration tab 192. The application tab198 may include multiple data destination components 118. Theapplication tab 198 may enable the user to select one or multiple datadestination components 118. The data destination components 118 mayinclude a local data center 110, the cloud-based data center 112, andvarious other applications or programs that may be used to store,organize, or analyze the data. The user may associate the new data model108 or specific components of the new data model 108 to one or multipledata destination components.

The selection of the application may include mapping one or moredatasets 120 of the data model 108 to one or multiple datasetsassociated with a second data model associated with a third-partyapplication. For example, FIG. 12 depicts a visualization 250 includingthe data model 108 and a second data model 252 associated with a thirdparty application. The second data model 252 may be selected by the userusing the applications tab 198 and the visualization 240 of FIG. 11. Insome embodiments, the user may use the described tools to describe aworkflow that coordinates how the datasets 120 are retrieved and storedbased on the transaction data 122. In this way, the datasets 120 may betailored to a specific third-party application in accordance to thetransaction data 122, which may be specified by the user. Indeed, thetransaction data 122 may be configurable, such that the datasets 120,conditions for collecting the datasets, and conditions for mapping thedatasets to a destination component 118 within the second data model 252may be configurable or set by a user.

It should be noted that the procedure 140, visualization 170,visualization 190, visualization 210, visualization 240, andvisualization 250 described above are provided for illustrative anddescriptive purposes and should not be used as limitations to the scopeof the disclosure. For instance, the procedure 140 may be performed inany viable order, some procedure steps may be added, and some of theaforementioned blocks may be removed partly depending on the applicationof the procedure. Any viable electronic display may be used with thecomputing device 24, including a non-graphical user interface. Theviable user interface may provide a coherent data flow between anindustrial automation system 10 and various data destination components118 in different embodiments.

As described above, the procedure 140 may be used for defining the datamodel 108 or a selected part of the data model 108 by the user.Referring now to FIG. 13, a process 280 may describe an example forrequesting and receiving data from the control system 22 using thedefined data model 108. For example, the computing device 24 may use thedata model 108 to provide contextualized data to a data requestor usingthe process 280 as described in detail below.

At block 282, the computing device 24 may receive a data request. Thedata request may be from the data destination component 118, based onthe transaction data 122, or both. As discussed above, the transactiondata 122 may define a trigger or threshold for a value in a dataset thatcauses the request to be sent from the data destination component 118.Alternatively, the computing device 24 may automatically generate therequest based on the value in the dataset meeting or exceeding thethreshold defined in the transaction data 122. For instance, if thedataset corresponds to pressure data, the transaction data 122associated with the pressure data may specify that the pressure datashould be sent to the data destination component 118 if the valueexceeds 2250 psa. In any case, in response to receiving the datarequest, the computing device 24 may use the data model 108 to identifya respective control system 22 associated with the requested data.

At block 284, the computing device 24 may submit the data request to therespective control system 22. In some embodiments, the request may beassociated with one or multiple respective control systems 22 and may beformatted in accordance with conditions specified in the transactiondata 122. That is, the transaction data 122 associated with therequested dataset may specify a communication protocol (e.g., requesttype, syntax, communication port) that the computing device 24 shoulduse to request access.

At block 286, the computing device 24 may receive raw data 114 from therespective control system 22. In some embodiments, the computing device24 may receive the raw data 114 with a respective data model, such asthe data model 108, from the respective control system 22. That is, thedata model 108 may be part of the metadata of the raw data 114, may bestored in a database accessible to the computing system 24, providedwith the request, part of the transaction data 122, or the like. Assuch, the computing device 24 may use the data model 108 to providecontext for the received raw data 114.

At block 288, the computing device 24 may send the requested data to thedata destination component 118. In some embodiments, the computingdevice 24 may organize the raw data according to the data model 108. Forexample, the computing device 24 may structure the received raw data 114with respect to the received data model 108 and send the structured rawdata 114 to the data destination component 118. For instance, if therequested raw data 114 is associated with a child node of anotherdataset, the computing device 24 may send the requested raw data 114with the datasets associated with the parent node.

In some embodiments, the computing device 24 may send the requested datato the data destination component 118 as structured data in accordancewith the data model 108 or with reference to the data model 108. In anycase, the data destination component 118 may, in turn, store the data inaccordance with the data model 108. As such, the data sets retrieved bythe data destination component 118 may maintain its context providing auser with a more comprehensive view of the relational nature of thedatasets.

By performing the embodiments described herein, computing systems maybind data sets, data models 108, and transaction data 122, such thatdata destination components 118 (e.g., applications) may efficientlycollect and organize data with its appropriate context. That is, thebinding process associates tags, models and transactions with aninstance of an application such that pre-defined properties or defaultsmay be utilized for storing and/or collecting datasets in an efficientmanner. Moreover, the present embodiments described herein enable newproperties to be entered by a user for a particular instance (e.g.,dataset) to allow datasets to be contextualized for more effective datapresentation. It should be noted that the structured context of thedatasets and the conditions of the transactions described herein enablethe respective computing devices to operate more efficiently bycoordinating the flow of data through limited network connectionbandwidths. Further, the contextualized data provides a specific formatin which datasets can be stored to enable users to understand and otherdevices to process the datasets more effectively.

While only certain features of the invention have been illustrated anddescribed herein, many modifications and changes will occur to thoseskilled in the art. It is, therefore, to be understood that the appendedclaims are intended to cover all such modifications and changes as fallwithin the true spirit of the invention.

1. An industrial system, comprising: a plurality of devices forperforming a plurality of operations in the industrial system; at leastone processor configured to perform operations comprising: accessing afirst device of the plurality of devices, wherein the first devicecomprises a plurality of datasets; determining whether a first datasetof the plurality of datasets is associated with an information model;receiving one or more inputs indicative of a first information modelassociated with the first dataset in response to the first dataset notbeing associated with the information model; and transferring the firstdataset and the first information model to another device of theplurality of devices.
 2. The system of claim 1, wherein the at least oneprocessor is configured to perform the operations comprisingtransferring the first dataset and the information model in response tothe first dataset being associated with the information model.
 3. Thesystem of claim 1, wherein the plurality of devices comprises one ormore sensors for providing information associated with the industrialsystem.
 4. The system of claim 1, wherein the at least one processor isconfigured to perform the operations comprising: retrieving transactiondata associated with the first device, wherein the transaction datacomprises a communication protocol to use to communicate with the firstdevice; and accessing the first device using the communication protocol.5. The system of claim 4, wherein the transaction data comprises acondition for transmitting the first dataset to the other device.
 6. Thesystem of claim 1, wherein the one or more inputs indicative of a firstinformation model comprises: receiving a first input indicative of oneor more components associated with the information model; receiving asecond input indicative of a hierarchical relationship between the firstdataset and the one or more components; and receiving a third inputindicative of one or more properties associated with at least one of theone or more components.
 7. The system of claim 6, wherein the one ormore properties are indicative of a first set of values associated withthe at least one of the one or more components, transaction data fortransferring the first dataset to another device of the plurality ofdevices, or both.
 8. The system of claim 1, wherein the at least oneprocessor is configured to perform the operations comprising receivingthe one or more inputs indicative of the first information modelassociated with the first dataset comprises selecting the firstinformation model from a list of information models associated with thefirst dataset.
 9. The system of claim 8, wherein the at least oneprocessor is configured to perform the operations comprising receiving amodification to one or more properties of the first information model.10. A method, comprising: detecting, by a computing device, one or morecontrol systems connected to the computing device; generating, by thecomputing device, a first visualization representative of the one ormore control systems; receiving, by the computing device, a first inputselecting a first control system of the one or more control systems viathe first visualization; generating, by the computing device, a secondvisualization representative of a list of data models based on the firstcontrol system; receiving, by the computing device, a second inputselecting one data model from the list of data models; storing, by thecomputing device, the one data model in a storage; generating, by thecomputing device, a third visualization representative of one or moredata destination components; receiving, by the computing device, a thirdinput selecting one data destination component of the one or more datadestination components; and sending, by the computing device, one ormore datasets associated with the first control system and the one datamodel to the one data destination component.
 11. The method of claim 10,comprising receiving transaction data associated with sending the onemore datasets to the one data destination component.
 12. The method ofclaim 11, wherein the transaction data comprises a communicationprotocol that the computing device uses to send the one or moredatasets.
 13. The method of claim 12, wherein the communication protocolcomprises FactoryTalk Live Data, EtherNet/IP, Common Industrial Protocol(CIP), OPC Direct Access, or any combination thereof
 14. The method ofclaim 10, comprising receiving a fourth input for defining a hierarchyof a plurality of component of the one data model.
 15. The method ofclaim 10, comprising associating raw data of the one or more datasets tothe one data model prior to sending the one or more datasets.
 16. Atangible, non-transitory, machine-readable medium, comprisingmachine-readable instructions that, when executed by a processor, causethe processor of an industrial automation system to perform actionscomprising: detecting one or more control systems connected to acomputing device; generating a first visualization representative of theone or more control systems; receiving a first input selecting a firstcontrol system of the one or more control systems via the firstvisualization; generating a second visualization representative of alist of data models based on the first control system; receiving asecond input selecting a data model from the list of data models;storing the selected data model in a storage; generating a thirdvisualization representative of one or more data destination components;receiving a third input selecting one data destination component of theone or more data destination components; and sending one or moredatasets associated with the first control system and the selected datamodel to the one data destination component.
 17. The tangible,non-transitory, machine-readable medium of claim 16, wherein theprocessor of the industrial automation system is configured to performthe actions comprising: receiving a fourth input defining a firstcomponent and a second component of a new data model; receiving a fifthinput defining a relationship between the first component and the secondcomponent, wherein the relationship is indicative that the secondcomponent is a child component to the first component; and receiving asixth input to associate raw data of the first control system to the newdata model components.
 18. The tangible, non-transitory,machine-readable medium of claim 16, wherein each data model from thelist of data models comprises a respective data structure, and whereineach respective data structures comprises a plurality of data sets, aplurality of components, a relationship each of between the plurality ofcomponents, one or more transaction conditions, or any combinationthereof
 19. The tangible, non-transitory, machine-readable medium ofclaim 18, wherein the transaction conditions comprise a communicationprotocol that the computing device uses to send the one or moredatasets.
 20. The tangible, non-transitory, machine-readable medium ofclaim 16, wherein the processor of the industrial automation system isconfigured to perform the actions comprising associating raw datareceived by the first control system to the data model.